🌳 Roadside Deforestation & Resilience: A Panarchy Framework¶
Assessing Socio-Ecological Impacts in Charghat using PRA & Geospatial Python¶
📝 Overview¶
This project investigates the severe socio-ecological crisis triggered by the widening of the Z-6006 Highway in Charghat, Rajshahi, which led to the removal of over 4,000 mature roadside trees.
Using the Panarchy Adaptive Cycle as a theoretical lens, the study integrates Participatory Rural Appraisal (PRA) with Geospatial Python (Google Earth Engine) to quantify the transition from a stable "Conservation" phase to a chaotic "Release" phase. The project assesses the cascading impacts—heat stress, air pollution, and livelihood loss—and co-designs a Locally Led Adaptation (LLA) framework to guide the system toward resilient "Renewal".
🎯 Objectives¶
- Objective 1: Assess physical, socio-economic, and environmental impacts using the Panarchy Theory (Conservation $\to$ Release $\to$ Reorganization).
- Objective 2: Validate community perceptions of heat and pollution using Remote Sensing (LST, NDVI, AOD).
- Objective 3: Develop a community-driven Nature-Based Solutions (NBS) framework for future resilience.
🛠️ Tools & Technologies¶
⚙️ Methodology¶
| Step | Description |
|---|---|
| 1. Data Collection | Primary: PRA tools (Social Mapping, FGDs, Problem Trees). Secondary: Satellite data via GEE (Sentinel-2, Landsat 8, MODIS, CHIRPS). |
| 2. Preprocessing | Used Python (geemap) to filter cloud cover, harmonize Sentinel-2 data, and compute indices (NDVI, AOD) clipped to the Charghat ROI. |
| 3. Analysis | Qualitative: Panarchy phase interpretation of community narratives. Spatial: Time-series analysis of LST (2016-2024) and Vegetation loss. |
| 4. Visualization | Created Sankey Diagrams to map causal flows of the crisis and Heatmaps to quantify stakeholder priorities. |
| 5. Validation | Triangulated PRA insights (e.g., "it feels hotter") with quantitative LST data (e.g., +5°C increase). |
Presentation¶
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📊 Results & Insights¶
- 🌍 System Collapse: The removal of trees triggered a "Release" phase, causing a sharp decline in NDVI and a spike in Aerosol Optical Depth (AOD).
- 📈 Heat Island Effect: Land Surface Temperature (LST) analysis revealed that summer temperatures in 2024 reached up to 39°C, a significant increase from the 2016 baseline.
- 🧭 Livelihood Shock: Code co-occurrence analysis showed that Livelihood Insecurity was the highest priority (100% intensity) for farmers and market vendors, overshadowing biodiversity concerns.
🗂️ Data Sources¶
| Source | Description | Link |
|---|---|---|
| Sentinel-2 | Vegetation Index (NDVI) 10m | Copernicus |
| Landsat 8 | Land Surface Temperature (LST) 30m | USGS EarthExplorer |
| MODIS Terra | Aerosol Optical Depth (AOD) | NASA Earthdata |
| Primary Data | FGD, KII, and Social Mapping | Field Survey (Charghat, 2024) |
🔖 Tags¶
Participatory Planning Geospatial Python Panarchy Theory Google Earth Engine Climate Resilience LST Analysis Nature-Based Solutions Rajshahi